Coverage remained the same at 89.274% when pulling5646146 on bnavigator:fix-594 into8b900ca on python-control:master.

#594 is fixed, as one can check manually.

But I am confused that4b44923 withoutf8fe08a cannot trigger a test failure.

And now I will really stop for today.

Found it:

>>> np.array(0.1)array(0.1)>>> np.array(0.1)*1J0.1j

Found it:

>>> np.array(0.1)array(0.1)>>> np.array(0.1)*1J0.1j

What is going on here? does np.array(0.1)*1 also return a scalar instead of an array?

I guess it is a somewhat less intuitive result of the broadcasting mechanics.

>>>import numpyas np>>> a=np.array(1.0)>>> aarray(1.)>>> a*1J1j>>> a*11.0>>>1*a1.0>>>1J*a1j>>> a+12.0>>>type(a)<class 'numpy.ndarray'>>>>type(1*a)<class 'numpy.float64'>>>>type(a*1J)<class 'numpy.complex128'>

https://numpy.org/doc/stable/reference/arrays.scalars.html